Goals and Objectives: The NIH Center for Interventional Oncology is an interdisciplinary effort with the primary goal of establishing an environment that will bring together multidisciplinary partners who will help define this emerging field of interventional oncology for minimally-invasive image-guided methods for treatment of locally-dominant cancer. This most often involves multi-disciplinary team science with clinician scientists, biomedical engineers, and other scientists joining approaches to try to solve unmet clinical needs. A separate report is filed within the NCI/CCR, since this multidisciplinary effort is supported by both NCI and CC. Project Summary: The NIH Center for Interventional Oncology is an interdisciplinary effort with the primary goal of developing and deploying novel local, regional, or combination cancer therapies in patients with localized or organ-confined neoplasms that may benefit from minimally-invasive image-guided therapies. The goals are achieved via collaborations between imaging scientists, interventional radiologists, oncologists (surgical, medical, radiation, or urological), biologists, chemists, and engineers. The CIO provides a translational environment wherein clinical shortcomings in oncology are identified, then addressed by a collaborative team that develop novel technologies and techniques. Minimally invasive therapies are often less costly, safer, and easy to translate and broadly apply in the setting of the NIH Clinical Center and Intramural Research Program. The Center for Interventional Oncology (CIO) was established in late FY 09 at the NIH Clinical Center (CC) to develop and translate image-guided technologies for localized cancer treatments. The Center is a collaboration involving the CC and the National Cancer Institute (NCI), and to lesser extent NIBIB. The Center draws on the strengths of each partner to investigate how imaging technologies and devices can diagnose and treat localized cancers in ways that are precisely targeted and minimally or non-invasive. It will also help bridge the gap between diagnosis and therapy, and between emerging technology and procedural medicine. Advanced imaging methods have ushered in an era of earlier detection of cancers that are frequently localized to a single organ or region, such as the liver. Interventional oncology often provides cancer patients with local or regional treatment options to augment the standard systemic treatment options like: immunotherapy, chemotherapy, surgery, and radiation. CIO investigators will leverage the interdisciplinary, translational environment at the CC to investigate and optimize how and when to combine drugs, devices, and multimodal imaging navigation. For example, activatable drugs can be injected in a vein or artery, then deployed directly in the tumor with needles or catheters using medical GPS, a technique that enables the physician to navigate through the body with real-time visualization using the latest advanced imaging technologies, such as magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), cone beam CT (CBCT), or ultrasound. Pre-procedural images are reused to guide devices delivering targeted therapy to the location of the disease, making the procedure more cost-effective because it doesn't require the imaging system to be physically present to take advantage of the information contained within. A prior prostate MRI, for example, can be used to help with guided biopsy or focal ablation by using a medical GPS-enabled needle and ultrasound, without requiring, occupying or tying up an MRI system during the procedure. In another example, a thin needle or sound waves can be used to ablate tumors and enhance targeted drug delivery. Energy sources include high-intensity focused ultrasound, freezing, microwaves, laser, and radiofrequency. Researchers also expand investigations into image-guided drug delivery or image-guided drug painting, where the image can be used to prescribe a particular drug to a specific region, by combining targeted, image-able-able or activate-able drugs with localized energy or heat to deploy the drug within specially engineered micro- or nano-particles. The Center provides a forum to encourage collaborations among researchers and patient-care experts in medical, surgical, urologic, and radiation oncology and interventional radiology. The CC provides an exceptional environment for this type of collaborative translational research and patient care. Other major program components include the development of new image-guided methods for personalized drug investigations (or tracking tissue responses to investigational drugs during drug discovery) and first-in-human investigations involving new drugs, devices, image-guided robotic assistance, and micro- and nano-sized drug vectors. Targeted sequential biopsy is a powerful tool for drug discover or biomarker characterization. Education and cross-training is another important part of the program. Significant gaps exist between the various disciplines, between research efforts and patient care, and between diagnosis and treatment. The gaps may be integrated through advanced image methods for localized therapy. CIO trainees augment existing training programs and underline the unique translational atmosphere at the NIH, where bench-to-bedside is the rule. Specific aims include: 1. Develop training and education in Interventional Oncology 2. Develop novel image-guided methods for smart biopsy and biomarker procurement to support targeted therapeutics 3. Support patient care using novel minimally invasive Interventional Oncology techniques 4. Pursue research in novel techniques and technologies in Interventional Oncology. This program is ideally and uniquely positioned to provide an interdisciplinary environment that combines training, patient care, and translational research to accelerate progress in interventional oncology and molecularly targeted interventions. The focus is upon translational models, translational tools, and actual practical deliverables of translation of multidisciplinary paradigms that meet specific clinical needs. A recent addition of artificial intelligence and deep learning in cancer was begun with the goal of integrating digital pathology, molecular and imaging information for specific cancers and cancer interventions. Other recent efforts have focused on characterization of methods to enhance immunotherapies with local or regional image guided therapies.